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Milestone 1 ArangoDB 3.3: Datacenter to Datacenter Replication

Estimated reading time: 6 minutes

Every company needs a disaster recovery plan for all important systems. This is true from small units like single processes running in some container to the largest distributed architectures. For databases in particular this usually involves a mixture of fault-tolerance, redundancy, regular backups and emergency plans. The larger a data store, the more difficult is it to come up with a good strategy.

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Setting up Datacenter to Datacenter Replication in ArangoDB

Estimated reading time: 7 minutes

Please note that this tutorial is valid for the ArangoDB 3.3 milestone 1 version of DC to DC replication!

Interested in trying out ArangoDB? Fire up your cluster in just a few clicks with ArangoDB ArangoGraph: the Cloud Service for ArangoDB. Start your free 14-day trial here

This milestone release contains data-center to data-center replication as an enterprise feature. This is a preview of the upcoming 3.3 release and is not considered production-ready.

In order to prepare for a major disaster, you can setup a backup data center that will take over operations if the primary data center goes..

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Auto-Generate GraphQL for ArangoDB

Estimated reading time: 4 minutes

Currently, querying ArangoDB with GraphQL requires building a GraphQL.js schema. This is tedious and the resulting JavaScript schema file can be long and bulky. Here we will demonstrate a short proof of concept that reduces the user related part to only defining the GraphQL IDL file and simple AQL queries.

The Apollo GraphQL project built a library that takes a GraphQL IDL and resolver functions to build a GraphQL.js schema. Resolve functions are called by GraphQL to get the actual data from the database. I modified the library in the way that before the resolvers are added, I read the IDL..

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Performance analysis with pyArango: Part II Inspecting transactions

Estimated reading time: 3 minutes

Following the previous blog post on performance analysis with pyArango, where we had a look at graphing using statsd for simple queries, we will now dig deeper into inspecting transactions. At first, we split the initialization code and the test code.

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Performance analysis using pyArango Part I

Estimated reading time: 6 minutes

This is Part I of Performance analysis using pyArango blog series. Please refer here for: Part II (cluster) and Part III (measuring system capacity).

Usually, your application will persist of a set of queries on ArangoDB for one scenario (i.e. displaying your user’s account information etc.) When you want to make your application scale, you’d fire requests on it, and see how it behaves. Depending on internal processes execution times of these scenarios vary a bit.

We will take intervals of 10 seconds, and graph the values we will get there:

  • average – all times measured during the interval,..
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A geo demonstration using Foxx

Estimated reading time: 2 minutes

Geo data is getting more and more important for today’s applications. The growing number of location-aware services, IoT applications and other solutions using latitude and longitude ask for precise and fast processing of geo data.

Let me show you in this quick demonstration how you can use geo functions and visualize your data using Foxx and leaflet.js.

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Sorting number strings numerically

Estimated reading time: 6 minutes

Recently I gave a talk about ArangoDB in front of a community of mathematicians. I advertised that nearly arbitrary data can “easily” be stored in a JSON based document store. The moment I had uttered the word “easily”, one of them asked about long integers. And if a mathematician says “long integer” they do not mean 64bit but “properly long”. He actually wanted to store orders of finite groups. I said one should use a JSON UTF-8 string for this but I should have seen the next question coming because he then wanted that a sorted index would actually sort the documents by the numerical value..

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Webinar: Use ArangoDB Agency as fault-tolerant persistent data store

Estimated reading time: 1 minutes

Join our Sr Distributed System Engineer, Kaveh Vahedipour, to learn more about ArangoDB Agency on September 19th, 2017 (6PM CEST/12PM ET/ 9AM PT)View the Recording.

Distributed systems have become the standard topology on which modern appliances live. While the advantages of distributing workload for both performance as well as fault-tolerance are obvious, the runtime flexible configuration of such deployment becomes non-trivial.

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VelocyStream 1.1 – async binary protocol

Estimated reading time: 2 minutes

With the 3.2 release, ArangoDB comes with version 1.1 of the binary protocol VelocyStream. VelocyStream is a bi-directional async binary protocol which supports sending messages pipelined, multiplexed, uni-directional or bi-directional. The messages themselves are VelocyPack objects.

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Pronto Move Shard

Estimated reading time: 5 minutes

In July Adobe announced that they plan the End-of-Life for flash at around 2020.As HTML5 progressed and due to a long history of critical security vulnerabilities this is – technologically speaking – certainly the right decision. However I tended to also become a bit sad.

Flash was the first technology that brought interactivity to the web. We tend to forget how static the web was in the early 2000s. Flash brought life to the web and there were plenty of stupid trash games and animations which I really enjoyed at the time. As a homage to the age of trashy flash games I created a game which..

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